Data reduction in the ITMS system through a data acquisition model with self-adaptive sampling rate

Long pulse or steady state operation of fusion experiments require data acquisition and processing systems that reduce the volume of data involved. The availability of self-adaptive sampling rate systems and the use of real-time lossless data compression techniques can help solve these problems. The former is important for continuous adaptation of sampling frequency for experimental requirements. The latter allows the maintenance of continuous digitization under limited memory conditions. This can be achieved by permanent transmission of compressed data to other systems. The compacted transfer ensures the use of minimum bandwidth. This paper presents an implementation based on intelligent test and measurement system (ITMS), a data acquisition system architecture with multiprocessing capabilities that permits it to adapt the system’s sampling frequency throughout the experiment. The sampling rate can be controlled depending on the experiment’s specific requirements by using an external dc voltage signal or by defining user events through software. The system takes advantage of the high processing capabilities of the ITMS platform to implement a data reduction mechanism based in lossless data compression algorithms which are themselves based in periodic deltas

Exact Bethe Ansatz solution for An−1A_{n-1} chains with non-SUq(n)SU_{q}(n) invariant open boundary conditions

The Nested Bethe Ansatz is generalized to open and independent boundary conditions depending on two continuous and two discrete free parameters. This is used to find the exact eigenvectors and eigenvalues of the $A_{n-1}$ vertex models and $SU(n)$ spin chains with such boundary conditions. The solution is found for all diagonal families of solutions to the reflection equations in all possible combinations. The Bethe ansatz equations are used to find de first order finite size correction.Comment: Two references adde

Web based system architecture for long pulse remote experimentation

Remote experimentation (RE) methods will be essential in next generation fusion devices. Requirements for long pulse RE will be: on-line data visualization, on-line data acquisition processes monitoring and on-line data acquisition systems interactions (start, stop or set-up modifications). Note that these methods are not oriented to real-time control of fusion plant devices. INDRA Sistemas S.A., CIEMAT (Centro de Investigaciones Energéticas Medioambientales y Tecnológicas) and UPM (Universidad Politécnica de Madrid) have designed a specific software architecture for these purposes. The architecture can be supported on the BeansNet platform, whose integration with an application server provides an adequate solution to the requirements. BeansNet is a JINI based framework developed by INDRA, which makes easy the implementation of a remote experimentation model based on a Service Oriented Architecture. The new software architecture has been designed on the basis of the experience acquired in the development of an upgrade of the TJ-II remote experimentation system

Event Recognition Using Signal Spectrograms in Long Pulse Experiments

As discharge duration increases, real-time complex analysis of the signal becomes more important. In this context, data acquisition and processing systems must provide models for designing experiments which use event oriented plasma control. One example of advanced data analysis is signal classification. The off-line statistical analysis of a large number of discharges provides information to develop algorithms for the determination of the plasma parameters from measurements of magnetohydrodinamic waves, for example, to detect density fluctuations induced by the Alfvén cascades using morphological patterns. The need to apply different algorithms to the signals and to address different processing algorithms using the previous results necessitates the use of an event-based experiment. The Intelligent Test and Measurement System platform is an example of architecture designed to implement distributed data acquisition and real-time processing systems. The processing algorithm sequence is modeled using an event-based paradigm. The adaptive capacity of this model is based on the logic defined by the use of state machines in SCXML. The Intelligent Test and Measurement System platform mixes a local multiprocessing model with a distributed deployment of services based on Jini

A versatile trigger and synchronization module with IEEE1588 capabilities and EPICS support.

Event timing and synchronization are two key aspects to improve in the implementation of distributed data acquisition (dDAQ) systems such as the ones used in fusion experiments. It is also of great importance the integration of dDAQ in control and measurement networks. This paper analyzes the applicability of the IEEE1588 and EPICS standards to solve these problems, and presents a hardware module implementation based in both of them that allow adding these functionalities to any DAQ. The IEEE1588 standard facilitates the integration of event timing and synchronization mechanisms in distributed data acquisition systems based on IEEE 803.3 (Ethernet). An optimal implementation of such system requires the use of network interface devices which include specific hardware resources devoted to the IEE1588 functionalities. Unfortunately, this is not the approach followed in most of the large number of applications available nowadays. Therefore, most solutions are based in software and use standard hardware network interfaces. This paper presents the development of a hardware module (GI2E) with IEEE1588 capabilities which includes USB, RS232, RS485 and CAN interfaces. This permits to integrate any DAQ element that uses these interfaces in dDAQ systems in an efficient and simple way. The module has been developed with Motorola's Coldfire MCF5234 processor and National Semiconductors's PHY DP83640T, providing it with the possibility to implement the PTP protocol of IEEE1588 by hardware, and therefore increasing its performance over other implementations based in software. To facilitate the integration of the dDAQ system in control and measurement networks the module includes a basic Input/Output Controller (IOC) functionality of the Experimental Physics and Industrial Control System (EPICS) architecture. The paper discusses the implementation details of this module and presents its applications in advanced dDAQ applications in the fusion community

Boundary K-matrices for the XYZ, XXZ AND XXX spin chains

The general solutions for the factorization equations of the reflection matrices $K^{\pm}(\theta)$ for the eight vertex and six vertex models (XYZ, XXZ and XXX chains) are found. The associated integrable magnetic Hamiltonians are explicitly derived, finding families dependig on several continuous as well as discrete parameters.Comment: 13 page

Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications

Analysis of NetCDF-4 and HDF-5 scientific file formats for the data archiving of ITER fast plant system controller prototype

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